Unscented Kalman Filter-Based Two-Stage Adaptive Compensation Method for Real-Time Hybrid Simulation

被引：0
|
作者：
Wang, Tao [1 ,2 ]
Gong, Yuefeng [1 ]
Xu, Guoshan [2 ,3 ,4 ]
Wang, Zhen [5 ]
机构：
[1] Heilongjiang Univ Sci & Technol, Sch Architecture & Civil Engn, Harbin, Peoples R China
[2] Harbin Inst Technol, Minist Educ, Key Lab Struct Dynam Behav & Control, Harbin, Peoples R China
[3] Harbin Inst Technol, Sch Civil Engn, Harbin 150090, Peoples R China
[4] Harbin Inst Technol, Minist Ind & Informat Technol, Key Lab Smart Prevent & Mitigat Civil Engn Disaste, Harbin, Peoples R China
[5] Wuhan Univ Technol, Sch Civil Engn & Architecture, Wuhan, Peoples R China
来源：
JOURNAL OF EARTHQUAKE ENGINEERING | 2024年 / 28卷 / 11期
基金：
中国国家自然科学基金;
关键词：
Real-time hybrid simulation; two-stage adaptive compensation; unscented Kalman filter; variable time delay; delay compensation; ACTUATOR DYNAMICS COMPENSATION; DELAY COMPENSATION; STABILITY ANALYSIS; DAMAGE DETECTION; SYSTEM;
D O I：
10.1080/13632469.2024.2335346
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
In order to effectively solve the dynamic delay problem of the servo-hydraulic actuator, simplify the design of the compensator, and improve the robustness of the compensation, an unscented Kalman filter-based two-stage adaptive compensation (UKF-TAC) method is proposed for real-time hybrid simulation (RTHS) in this study. Theoretical analysis and numerical simulations are conducted to verify the performance of the proposed UKF-TAC method. The research results show that the proposed UKF-TAC method can significantly simplify the design of the compensator, effectively improve the compensation accuracy, and has the robustness to adapt to different partitioning cases and resist the interference of uncertain factors.
引用
收藏
页码：3221 / 3255
页数：35
相关论文
共 50 条
  • [31] An Adaptive Spatial Target Tracking Method Based on Unscented Kalman Filter
    Rong, Dandi
    Wang, Yi
    Sensors, 2024, 24 (18)
  • [32] REAL-TIME TRAJECTORY ESTIMATION OF SPACE LAUNCH VEHICLE USING EXTENDED KALMAN FILTER AND UNSCENTED KALMAN FILTER
    Baek, Jeong-Ho
    Park, Sang-Young
    Park, Eun-Seo
    Choi, Kyu-Hong
    Lim, Hyung-Chul
    Park, Jong-Uk
    JOURNAL OF ASTRONOMY AND SPACE SCIENCES, 2005, 22 (04) : 501 - 512
  • [33] Adaptive compensation method for real-time hybrid simulation of train-bridge coupling system
    Zhou, Hui M.
    Zhang, Bo
    Shao, Xiao Y.
    Tian, Ying P.
    Guo, Wei
    Gu, Quan
    Wang, Tao
    STRUCTURAL ENGINEERING AND MECHANICS, 2022, 83 (01) : 93 - 108
  • [34] Unscented Kalman filter-based method for spacecraft navigation using resident space objects
    Driedger M.
    Rososhansky M.
    Ferguson P.
    Aerospace Systems, 2020, 3 (3) : 197 - 205
  • [35] TWO-STAGE PARAMETRIC IDENTIFICATION PROCEDURE FOR A SATELLITE MOTION MODEL BASED ON ADAPTIVE UNSCENTED KALMAN FILTERS
    Chernikova, O. S.
    Grechkoseev, A. K.
    Danchenko, I. G.
    BULLETIN OF THE SOUTH URAL STATE UNIVERSITY SERIES-MATHEMATICAL MODELLING PROGRAMMING & COMPUTER SOFTWARE, 2022, 15 (04): : 32 - 43
  • [36] Real-time tuning unscented kalman filter for a redundant attitude estimator in microsatellites
    Laboratory for Space Systems, Tokyo Institute of Technology, Tokyo, Japan
    不详
    Trans Jpn Soc Aeronaut Space Sci, 2013, 6 (360-368):
  • [37] A Method for Real-Time Estimating Pose of Large Aircraft Component in Process of Pose Adjustment based on the Unscented Kalman Filter
    Ying, Zheng
    SMART MATERIALS AND INTELLIGENT SYSTEMS, 2012, 442 : 251 - 255
  • [38] Real-time train motion parameter estimation using an Unscented Kalman Filter
    Cunillera, Alex
    Besinovic, Nikola
    van Oort, Niels
    Goverde, Rob M. P.
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2022, 143
  • [39] Unscented Kalman Filter for UAV Real-Time Localizating Dynamic Target on the Ground
    Zhou, Xuyang
    Sun, Wei
    He, Ruofei
    Liu, Hongjuan
    ADVANCES IN INTELLIGENT INFORMATION HIDING AND MULTIMEDIA SIGNAL PROCESSING (IIH-MSP 2021 & FITAT 2021), VOL 2, 2022, 278 : 55 - 65
  • [40] Real-Time Noninvasive Intracranial State Estimation Using Unscented Kalman Filter
    Park, Chanki
    Ryu, Seung Jun
    Jeong, Bong Hyun
    Lee, Sang Pyung
    Hong, Chang-Ki
    Kim, Yong Bae
    Lee, Boreom
    IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2019, 27 (09) : 1931 - 1938
12345